Learning poverty

Mekko shifted

Photo by Nikhita S on Unsplash

Education is the most powerful weapon you can use to change the world…
— Nelson Mandela

Ingest

# Create dataset
df = read_csv("archetypes/goal-4-quality-education.csv")
df

Wrangle

Steps:
* replace cell “890k” with “0.89” in “out of school” column and convert column to numeric
* drop unnecessary columns
* calculate total students by region, for the world, and calculate percentages
* create a “diplay region” to help with labels on plot

df_final <- df %>%
  mutate(out_of_school = as.numeric(if_else(`Learning poor - out of school` == "890k", "0.89", `Learning poor - out of school`))) %>%
  select(region = Region, learning_proficient = `Not learning poor`, 
         learning_not_proficient = `Learning poor - students below minimum proficiency level`, out_of_school) %>%
  group_by(region) %>%
  mutate(total_children_by_region = learning_proficient + learning_not_proficient + out_of_school) %>%
  ungroup() %>%
  group_by() %>%
  mutate(world_children_total = sum(learning_proficient) + sum(learning_not_proficient) + sum(out_of_school)) %>%
  ungroup() %>%
  mutate(percent_children_over_world = 100 * total_children_by_region / world_children_total,
         percent_learning_proficient = 100 * learning_proficient / total_children_by_region,
         percent_learning_not_proficient = 100 * learning_not_proficient / total_children_by_region,
         percent_out_of_school = 100 * out_of_school / total_children_by_region,
         xmax = cumsum(percent_children_over_world),
         xmin = xmax - percent_children_over_world) %>%
  mutate(display_region = case_when(region == "Europe & Central Asia" ~ "Europe\n & \n Central\n Asia",
                                    region == "Latin America & Caribbean" ~ "Latin \nAmerica\n & \nCaribbean",
                                    region == "Sub-Saharan Africa" ~ "Sub-Saharan \nAfrica",
                                    region == "Middle East & North Africa" ~ "Middle\n East\n & \nNorth \nAfrica",
                                    TRUE ~ region))

df_final

Plot

final result

theme_opts <- theme(
    text = element_text(family = "inconsolata", size = 16), 
    plot.title = element_text(color = "black", size = 16, face = "bold"),
    plot.subtitle = element_text(color = "black", size = 12),
    plot.caption = element_text(color = "#555555", size = 10),
    panel.border = element_blank(),
    plot.background = element_blank(),
    panel.background = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.minor.x = element_blank(),
    panel.grid.major.y = element_blank(),
    panel.grid.minor.y = element_blank(),
    legend.title = element_blank(),
    axis.title.x = element_blank(),
    axis.text.x = element_blank(),
    axis.ticks.x = element_blank(),
    axis.title.y = element_blank(),
    legend.position = "top"
)

fill_colors <- c("Not learning poor" = "#95AEBF", 
                 "Learning poor - students below minimum proficiency level" = "#D7CE59", 
                 "Learning poor - out of school" = "#96553E")


v1 <- ggplot(df_final) +
    geom_segment(aes(x=0, xend=100, y=20, yend=20), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=40, yend=40), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=60, yend=60), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=80, yend=80), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=100, yend=100), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=-20, yend=-20), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=-40, yend=-40), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=-60, yend=-60), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=-80, yend=-80), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=-100, yend=-100), colour = "grey") +
    geom_rect(aes(ymin = 0, ymax = percent_learning_proficient, xmin = xmin, xmax = xmax,
                  fill = "Not learning poor"), 
              color = "white") +
    geom_rect(aes(ymin = 0, ymax = -percent_learning_not_proficient, xmin = xmin, xmax = xmax,
                  fill = "Learning poor - students below minimum proficiency level"), 
              color = "white") +
    geom_rect(aes(ymin = -percent_learning_not_proficient, 
                  ymax = -(percent_learning_not_proficient +percent_out_of_school), 
                  xmin = xmin, xmax = xmax,
                  fill = "Learning poor - out of school"), 
              color = "white") +
    scale_fill_manual(values = fill_colors)+
  geom_text(aes(x=(xmin+xmax)/2, 
                y=-(percent_learning_not_proficient + percent_out_of_school), 
                label=display_region),
            vjust = "top", family = "inconsolata") +
  geom_segment(aes(x=40, xend=60.13253, y=50, yend=50),
    size=0.5, arrow = arrow(length=unit(0.30,"cm"), type = "closed")
  )+
  geom_segment(aes(x=40, xend=28.36854, y=50,yend=50),
    size=0.5, arrow = arrow(length=unit(0.30,"cm"), type = "closed")
  ) +
  annotate("text", x=45, y=60, 
           label="Width of bar represents population\nof children in each region", family = "inconsolata") +
  geom_segment(aes(x=-1, xend=-1, y=0, yend=10),
    size=0.5, arrow = arrow(length=unit(0.30,"cm"), type = "closed")
  ) +
  geom_segment(aes(x=-1, xend=-1, y=0, yend=-10),
    size=0.5, arrow = arrow(length=unit(0.30,"cm"), type = "closed")
  ) +
  annotate("text", x=1, y=5,
           label="Not learning poor",
           hjust = 0, family = "inconsolata") +
  annotate("text", x=1, y=-5, 
           label="Learning poor",
           hjust = 0, family = "inconsolata") +
  geom_segment(aes(x=-1, xend=100, y=0, yend=0)) + 
  scale_y_continuous(breaks = seq(-100, 100, by = 20),
                     labels = function(x) paste0(x, "%")) +
  scale_x_continuous(expand = c(0.01, 0)) +
  labs(title = "Learning poverty in low- and middle-income countries varies by region",
       subtitle = "Share of children at the end of primary school age (ages 10-14), by learning category, 2015 (%)") +
    theme_bw() +
    theme_opts 

girafe(ggobj = v1, width_svg = 13, height_svg = 7,
       options = list(opts_sizing(rescale = TRUE, width = 1.0)))

Step-by-Step

shapes

fill_colors <- c("Not learning poor" = "#95AEBF", 
                 "Learning poor - students below minimum proficiency level" = "#D7CE59", 
                 "Learning poor - out of school" = "#96553E")


v2 <- ggplot(df_final) +
    geom_segment(aes(x=0, xend=100, y=20, yend=20), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=40, yend=40), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=60, yend=60), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=80, yend=80), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=100, yend=100), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=-20, yend=-20), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=-40, yend=-40), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=-60, yend=-60), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=-80, yend=-80), colour = "grey") +
    geom_segment(aes(x=0, xend=100, y=-100, yend=-100), colour = "grey") +
    geom_rect(aes(ymin = 0, ymax = percent_learning_proficient, xmin = xmin, xmax = xmax,
                  fill = "Not learning poor"), 
              color = "white") +
    geom_rect(aes(ymin = 0, ymax = -percent_learning_not_proficient, xmin = xmin, xmax = xmax,
                  fill = "Learning poor - students below minimum proficiency level"), 
              color = "white") +
    geom_rect(aes(ymin = -percent_learning_not_proficient, 
                  ymax = -(percent_learning_not_proficient +percent_out_of_school), 
                  xmin = xmin, xmax = xmax,
                  fill = "Learning poor - out of school"), 
              color = "white") +
    scale_fill_manual(values = fill_colors) +
    theme_bw() +
    theme_opts 

girafe(ggobj = v2, width_svg = 13, height_svg = 7,
       options = list(opts_sizing(rescale = TRUE, width = 1.0)))

shapes, labels, and annotations

v3 <- v2 +
  geom_text(aes(x=(xmin+xmax)/2, 
                y=-(percent_learning_not_proficient + percent_out_of_school), 
                label=display_region),
            vjust = "top", family = "inconsolata") +
  geom_segment(aes(x=40, xend=60.13253, y=50, yend=50),
    size=0.5, arrow = arrow(length=unit(0.30,"cm"), type = "closed")
  )+
  geom_segment(aes(x=40, xend=28.36854, y=50,yend=50),
    size=0.5, arrow = arrow(length=unit(0.30,"cm"), type = "closed")
  ) +
  annotate("text", x=45, y=60, 
           label="Width of bar represents population\nof children in each region", family = "inconsolata") +
  geom_segment(aes(x=-1, xend=-1, y=0, yend=10),
    size=0.5, arrow = arrow(length=unit(0.30,"cm"), type = "closed")
  ) +
  geom_segment(aes(x=-1, xend=-1, y=0, yend=-10),
    size=0.5, arrow = arrow(length=unit(0.30,"cm"), type = "closed")
  ) +
  annotate("text", x=1, y=5, 
           label="Not learning poor",
           hjust = 0, family = "inconsolata") +
  annotate("text", x=1, y=-5, 
           label="Learning poor",
           hjust = 0, family = "inconsolata") +
  geom_segment(aes(x=-1, xend=100, y=0, yend=0)) + 
  scale_y_continuous(breaks = seq(-100, 100, by = 20),
                     labels = function(x) paste0(x, "%")) +
  scale_x_continuous(expand = c(0.01, 0)) +
  labs(title = "Learning poverty in low- and middle-income countries varies by region",
       subtitle = "Share of children at the end of primary school age (ages 10-14), by learning category, 2015 (%)") +
  theme_bw() +
  theme_opts 

girafe(ggobj = v3, width_svg = 13, height_svg = 7,
       options = list(opts_sizing(rescale = TRUE, width = 1.0)))

References

The citations and data sources used for this case

Narrative and Data sources: World Bank - Learning poverty: children’s education in crisis, GO